Simultaneous Localization of Robots and Mapping of Wireless Sensor Nodes

  • Andrea Zanella
  • Emanuele Menegatti
Part of the Studies in Computational Intelligence book series (SCI, volume 554)


This chapter presents the use of a mobile robot to solve the problem of node localization in Wireless Sensor Network (WSN). The algorithms we propose are inspired by the algorithms developed in robotics to solve the robot localization problem exploiting landmarks in the environment. The robotics community developed algorithms of Simultaneous Localization and Mapping (SLAM), in which the robot pose is estimated while simultaneously mapping the position of the landmarks in the environment. Similarly, we simultaneously estimate the robot pose with the position of the nodes of a WSN using range measurements. The assumption is that a mobile robot can estimate the distance to nearby nodes of the WSN by measuring the Radio Signal Strenght (RSS) of the received radio messages. The intrinsic variability of RSS measurements due to interferences and reflections of radio signals, however, makes the ranging measure very noisy, thus limiting the accuracy of simple localization techniques. We first present a SLAM technique based on an Extended Kalman Filter (EKF-SLAM) to integrate RSS measurements from the different nodes over time, while the robot moves in the environment. Successively, we show that combining the EKF-SLAM algorithm with an initialization phase based on a Delayed Particle Filter (DPF) can greatly improve the performance of the algorithm. We then discuss possible extensions of the approach by using advanced RSS measurement techniques, and multidimensional scaling localization. Finally, we compare the different approaches on the same experimental testbed, both for indoor and outdoor scenarios.


Sensor Node Wireless Sensor Network Mobile Robot Mobile Node Extend Kalman Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Sichitiu, M., Ramadurai, V.: Localization of wireless sensor networks with a mobile beacon. In: 2004 IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, pp. 174–183 (2004)Google Scholar
  2. 2.
    Menegatti, E., Zanella, A., Zilli, S., Zorzi, F., Pagello, E.: Range-only SLAM with a mobile robot and a Wireless Sensor Networks. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 8–14 (May 2009)Google Scholar
  3. 3.
    Montemerlo, M., Thrun, S.: FastSLAM: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics. Springer (January 2007)Google Scholar
  4. 4.
    Menegatti, E., Danieletto, M., Mina, M., Pretto, A., Bardella, A., Zanella, A., Zanuttigh, P.: Discovery, localization, and recognition of smart objects by a mobile robot. In: Ando, N., Balakirsky, S., Hemker, T., Reggiani, M., von Stryk, O. (eds.) SIMPAR 2010. LNCS, vol. 6472, pp. 436–448. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  5. 5.
    Menegatti, E., Danieletto, M., Mina, M., Pretto, S., Zanconato, A., Zanuttigh, P., Zanella, A.: Autonomous discovery, localization and recognition of smart objects through WSN and image features. In: Proc. of: IEEE International Workshop Towards Smart Communications and Network technologies applied on Autonomous Systems (SaCoNAS), IEEE GLOBECOM (2010)Google Scholar
  6. 6.
    Bardella, A., Danieletto, M., Menegatti, E., Zanella, A., Pretto, A., Zanuttigh, P.: Autonomous robot exploration in smart environments exploiting wireless sensors and visual features. Annals of Telecommunications 67(7-8), 1–15 (2012), doi:10.1007/s12243-012-0305-zCrossRefGoogle Scholar
  7. 7.
    Thelen, J., Goense, D., Langendoen, K.: Radio wave propagation in potato fields. In: First workshop on Wireless Network Measurements (co-located with WiOpt 2005), Riva del Garda, Italy (2005)Google Scholar
  8. 8.
    Zanella, A., Bardella, A.: RSS-based ranging by multichannel RSS averaging. IEEE Wireless Communications Letters (2013), doi:10.1109/WCL.2013.100913.130631Google Scholar
  9. 9.
    Bahl, P., Padmanabhan, V.: Radar: an in-building RF-based user location and tracking system. In: Proceedings of the IEEE INFOCOM 2000, vol. 2, pp. 775–784 (2000)Google Scholar
  10. 10.
    Kurth, D., Kantor, G., Singh, S.: Experimental results in range-only localization with radio. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), vol. 1, pp. 974–979 (October 2003)Google Scholar
  11. 11.
    Pathirana, P., Bulusu, N., Savkin, A., Jha, S.: Node localization using mobile robots in delay-tolerant sensor networks. IEEE Transactions on Mobile Computing 4(3), 285–296 (2005)CrossRefGoogle Scholar
  12. 12.
    Goldsmith, A.: Wireless Communications. Cambridge University Press (2005)Google Scholar
  13. 13.
    Djugash, J., Singh, S., Kantor, G., Zhang, W.: Range-only slam for robots operating cooperatively with sensor networks. In: Proceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006, pp. 2078–2084 (2006)Google Scholar
  14. 14.
    Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. In: Intelligent Robotics and Autonomous Agents. The MIT Press (August 2005)Google Scholar
  15. 15.
    Corke, P., Hrabar, S., Peterson, R., Rus, D., Saripalli, S., Sukhatme, G.: Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2004), April 26-May 1, vol. 4, pp. 3602–3608 (2004)Google Scholar
  16. 16.
    Bardella, A., Bui, N., Zanella, A., Zorzi, M.: An experimental study on IEEE 802.15. 4 multichannel transmission to improve RSSbased service performance. In: Proceedings of Real-World Wireless Sensor Networks, pp. 154–161. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  17. 17.
    Costa, J.A., Patwari, N., Hero III, A.O.: Distributed weighted-multidimensional scaling for node localization in sensor networks. ACM Transactions Sensor Networks 2, 39–64 (2006)CrossRefGoogle Scholar
  18. 18.
    Crepaldi, R., Harris, A., Scarpa, A., Zanella, A., Zorzi, M.: Signetlab: deployable sensor network testbed and management tool. In: Proceedings of the 4th ACM International Conference on Embedded Networked Sensor Systems (SenSys 2006), New York, NY, USA, pp. 375–376 (2006)Google Scholar
  19. 19.
    Crepaldi, R., Harris, A., Scarpa, A., Zanella, A., Zorzi, M.: Testbed implementation and refinement of a range-based localization algorithm for wireless sensor networks. In: 3rd IEE Mobility Conference 2006, October 25-27 (2006)Google Scholar
  20. 20.
    Kraetzschmar, G.K., Utz, H., Sablatnög, S., Enderle, S., Palm, G.: Miro - middleware for cooperative robotics. In: Birk, A., Coradeschi, S., Tadokoro, S. (eds.) RoboCup 2001. LNCS (LNAI), vol. 2377, pp. 411–416. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  21. 21.
    Utz, H., Sablatnog, S., Enderle, S., Kraetzschmar, G.: Miro - middleware for mobile robot applications. IEEE Transactions on Robotics and Automation 18(4), 493–497 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Information EngineeringUniversity of PadovaPadovaItaly

Personalised recommendations